2025 ASEE Annual Conference & Exposition

Rapid technological advancements, including the emergence of computer-aided design and simulation, have had a significant impact on the engineering industry. This, in turn, extends to engineering education, demonstrating a similar influential effect. The latest development to have such reverberations is the launch of a generative artificial intelligence (AI) chatbot known as ChatGPT. ChatGPT utilizes a large language model (LLM) that trains the platform to understand and generate human-like responses. This LLM comprises numerous neural networks trained using the vast amount of information available online, including research papers. As this new technology is widely accessible to students, the questions that arise regarding its role in education are almost always related to academic integrity. ChatGPT can answer questions, compose and revise papers (like this one), and complete collegiate course evaluations. Though ChatGPT can be misused, like many tools, when used as intended, it can assist students in their educational efforts. That is, instead of asking AI to answer homework prompts, one can inquire for clarification to further their knowledge about nuanced engineering phenomena.

This paper attempts to understand students' perspectives and engagement with generative AI in a university-level introductory engineering course. Self-reported student data were collected through a survey and six focus group interviews, which were then thematically coded to elucidate any common trends. Unsurprisingly, students admitted to copying and pasting assignment questions into AI but soon discovered that the answers were, more often than not, unreliable. This feedback forced them to use it more productively. Interestingly, many students viewed AI as an around-the-clock tutor that was conveniently always available, asking it to clarify complex topics or provide definitions or equations needed for assignments. A substantial number of responses indicated that students found AI helpful when preparing for exams, as it helped formulate study guides by synthesizing student-inputted equation sheets or created practice problems that mimicked exam questions.